通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026
通用机器学习:unsupervised_and_semisupervised_learning
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 2,683 篇被归入该主题的论文。
主要结论
- 通用机器学习 · unsupervised and semisupervised learning论文从 2023 年的 649 篇增长到 2026 年的 799 篇,三年间扩大到约 1.2 倍。
- ICML 是发通用机器学习 · unsupervised and semisupervised learning论文最多的会议,2023–2026 年共 859 篇,占四个会议总量的 32%。
- 交叉方向里涨得最快的是深度学习 · self supervised learning:同时属于两个主题的论文从 2023 年的 23 篇增至 2026 年的 86 篇。
- 在「通用机器学习」的 6 个主题里,它的 2026 年论文数排第 1;同组增长最快的通用机器学习 · evaluation是 4.3 倍,通用机器学习 · unsupervised and semisupervised learning是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
代表论文
按年份和会议均匀挑选,方便快速看到每一届的样貌
- NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
- ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
- ICLR 2026A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data
- CVPR 2026COG Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object
- NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
- ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
- ICLR 2025A General Framework for Producing Interpretable Semantic Text Embeddings
- CVPR 2025A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening
- NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
- ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
- ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
- CVPR 2024Dual Prototype Attention for Unsupervised Video Object Segmentation
- NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
- ICML 2023A Mathematical Model for Curriculum Learning for Parities
- ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
- CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
- NeurIPS 2026Attention-based PCA
- ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
- ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
- CVPR 2026CROWn A Unified Framework for Anti-Aliased Downsampling and Phase-Calibrated Fusion
全部通用机器学习 · unsupervised and semisupervised learning论文
共 833 篇,第 7 / 17 页
- NeurIPS 2025Looking Into the Water by Unsupervised Learning of the Surface Shape
- NeurIPS 2025LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
- NeurIPS 2025Luminance-Aware Statistical Quantization: Unsupervised Hierarchical Learning for Illumination Enhancement
- NeurIPS 2025MAP Estimation with Denoisers: Convergence Rates and Guarantees
- NeurIPS 2025Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
- NeurIPS 2025MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning
- NeurIPS 2025Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
- NeurIPS 2025Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning
- NeurIPS 2025Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
- NeurIPS 2025Multiresolution Analysis and Statistical Thresholding on Dynamic Networks
- NeurIPS 2025Nearly-Linear Time and Massively Parallel Algorithms for $k$-anonymity
- NeurIPS 2025Neural Fractional Attention Differential Equations
- NeurIPS 2025Neural Mutual Information Estimation with Vector Copulas
- NeurIPS 2025Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data
- NeurIPS 2025Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shift with Unlabeled Data
- NeurIPS 2025OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction
- NeurIPS 2025On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
- NeurIPS 2025On the Hardness of Conditional Independence Testing In Practice
- NeurIPS 2025On the Loss of Context Awareness in General Instruction Fine-tuning
- NeurIPS 2025On the Relation between Rectified Flows and Optimal Transport
- NeurIPS 2025Online Learning of Pure States is as Hard as Mixed States
- NeurIPS 2025Optimal Graph Clustering without Edge Density Signals
- NeurIPS 2025Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
- NeurIPS 2025Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
- NeurIPS 2025Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
- NeurIPS 2025Parameter Dynamics of Online Machine Learning and Test-time Adaptation
- NeurIPS 2025Precise Asymptotics and Refined Regret of Variance-Aware UCB
- NeurIPS 2025Preference Learning with Response Time: Robust Losses and Guarantees
- NeurIPS 2025Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization
- NeurIPS 2025RankSEG-RMA: An Efficient Segmentation Algorithm via Reciprocal Moment Approximation
- NeurIPS 2025Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
- NeurIPS 2025Restoring Pruned Large Language Models via Lost Component Compensation
- NeurIPS 2025Rethinking Hebbian Principle: Low-Dimensional Structural Projection for Unsupervised Learning
- NeurIPS 2025Rethinking Out-of-Distribution Detection and Generalization with Collective Behavior Dynamics
- NeurIPS 2025Rethinking PCA Through Duality
- NeurIPS 2025RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees
- NeurIPS 2025Robust Label Proportions Learning
- NeurIPS 2025Robust Regression of General ReLUs with Queries
- NeurIPS 2025Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning
- NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
- NeurIPS 2025Sampled Estimators For Softmax Must Be Biased
- NeurIPS 2025Scalable and adaptive prediction bands with kernel sum-of-squares
- NeurIPS 2025Scalable Signature Kernel Computations via Local Neumann Series Expansions
- NeurIPS 2025Señorita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists
- NeurIPS 2025Separating the 'what' and 'how' of compositional computation to enable reuse and continual learning
- NeurIPS 2025Shapley-Based Data Valuation for Weighted $k$-Nearest Neighbors
- NeurIPS 2025SHGR: A Generalized Maximal Correlation Coefficient
- NeurIPS 2025SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
- NeurIPS 2025SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration
- NeurIPS 2025Spatiotemporal Consensus with Scene Prior for Unsupervised Domain Adaptive Person Search
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · unsupervised and semisupervised learning在 ICML 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "gml-unsupervised-and-semisupervised-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- 共 2,683 篇,按年份分别是 2023 年 649 篇、2024 年 553 篇、2025 年 682 篇、2026 年 799 篇。
- NeurIPS 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- NeurIPS 2026 有 194 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 203 篇。
- ICLR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- ICLR 2026 有 187 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 174 篇。
- ICML 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- ICML 2026 有 348 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 239 篇。
- CVPR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文?
- CVPR 2026 有 70 篇通用机器学习 · unsupervised and semisupervised learning论文,上一届是 66 篇。
- 哪个会议的通用机器学习 · unsupervised and semisupervised learning论文最多?
- ICML,2023–2026 年共 859 篇。